Please use this identifier to cite or link to this item: https://scholarhub.balamand.edu.lb/handle/uob/583
Title: Fuzzy ARTVar : an improved fuzzy ARTMAP algorithm
Authors: Dagher, Issam 
Georgiopoulos, M
Heileman, G.L
Bebis, G
Affiliations: Department of Computer Engineering 
Keywords: Generalisation (artificial intelligence),
Fuzzy neural nets
ART neural nets
Pattern classification
Learning (artificial intelligence)
Subjects: Performance--Evaluation
Issue Date: 2002
Publisher: IEEE
Part of: IEEE World Congress on Computational Intelligence. IEEE International Joint Conference on Neural Networks Proceedings
Start page: 1688
End page: 1693
Conference: IEEE International Joint Conference on Neural Networks (4-9 May 1998 : Anchorage, AK, USA) 
Abstract: 
We introduce a variation of the performance phase of fuzzy ARTMAP which is called Fuzzy ARTVar. Experimental results have shown that Fuzzy ARTVar exhibits superior generalization performance, compared to fuzzy ARTMAP, for a variety of machine learning databases. Furthermore, experimental results have also demonstrated that Fuzzy ARTVar compares favourably with other existing variations of fuzzy ARTMAP, such as ARTEMAP (power rule), ARTEMAPQ (Q-max rule), and Gaussian ARTMAP. The performance of Fuzzy ARTVar is independent of the tuning of network parameters, which is in contrast with the ARTEMAP, ARTEMAPQ, and Gaussian ARTMAP algorithms, whose performance depends on the choice of certain network parameters.
URI: https://scholarhub.balamand.edu.lb/handle/uob/583
Type: Conference Paper
Appears in Collections:Department of Computer Engineering

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